Beyond Bias: Non-Exclusion Duties for AI-Enabled Public Services

DOI

10.2991/978-2-38476-547-8_21How to use a DOI?

Keywords

Digital inequality; social stratification; algorithmic decision-making

Abstract

Artificial intelligence (AI) makes more and more important opportunities and services, such as welfare benefits, health care in the form of triage, educational assistance, employment, housing, banking, and legal services, available. Contemporary debates on fair AI tend to revolve around statistical discrimination and discriminatory outcomes. This paper will argue that this framework is normatively insufficient: although accurate and non-discriminatory AI systems can make inequality worse, they can also be used as a flawed social infrastructure, or as gatekeeping mechanisms that can more or less enable or block participation. Based on sociological studies on digital stratification and political science challenges of legitimacy and equal rights, the paper conceptualizes AI access in multi-dimensionality: material access (devices, connectivity, time), capability access (language, literacy, disability inclusion), and institutional access (rules, documentation burdens, and availability of appeal and assistance). The paper constructs a system of rights and duties on the foundations of two notions: Minimum Access Guarantees (guarantees availability of the minimum service without the presence of unreasonable restrictions created by AI) and Non-Exclusion Duties (duty obligations to avoid foreseeable exclusion, regardless of the intent of discrimination). The concepts are applied through four principles of governance, namely: (1) AI-optional baseline routes, (2) capability-sensitive design as a condition, (3) non-punitive access, and (4) responsibility of infrastructural damages through contestability, redress, and supervision. The article ends with the duty separating between the role of public agencies and major predominant private gateway actors, and gives a practical checklist on gauging AI implementations when access is a necessity.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Vikas Waghmare
PY  - 2026
DA  - 2026/03/05
TI  - Beyond Bias: Non-Exclusion Duties for AI-Enabled Public Services
BT  - Proceedings of the International Conference on Socio Legal Intricacies of Artificial Intelligence (ICSLIAI 2026)
PB  - Atlantis Press
SP  - 176
EP  - 182
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-547-8_21
DO  - 10.2991/978-2-38476-547-8_21
ID  - Waghmare2026
ER  -